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• Connection between Acuna Analytics (former company) and GoSquared (previous startup) |
• Discussion about past experiences with analytics and monitoring systems (GoSquared, MongoDB, Cassandra, Graphite) |
• Comparison of scalability and limitations of various systems (Graphite, Prometheus, Cortex) |
• Mention of Acuna's contribution to the Cassandra project (virtual nodes technique) |
• Connection between Cassandra/Graphite and modern systems (Cortex, Loki, Tempo) |
• Reflection on the evolution of analytics and monitoring technology |
• Debate about the definition of observability and its relationship to metrics, logs, and traces |
• Discussion of the importance of curiosity and understanding system behavior for observability |
• Grafana Labs avoids one-size-fits-all solutions and instead supports multiple tools and combinations to help users get the best results |
• The goal is to bring together different teams' tools into a single place with a unified experience |
• The ideal tool helps users access data and test hypotheses, rather than providing automation or root cause analysis |
• Situationally-appropriate tool selection depends on the problem and available tools |
• The speaker mentions a colleague named Manu who was previously involved with the Phoenix app and is now at a cryptocurrency company. |
• The speaker explains that the Phoenix app is monolithic, meaning it's not broken down into microservices, and has a specific architecture involving a CDN, load balancer, Ingress Nginx, and a database. |
• The speaker discusses the importance of instrumenting the system to collect metrics and troubleshoot slow requests. |
• The speaker mentions using Prometheus and exporters to collect metrics from various components of the system. |
• The speaker explores integrating Fastly logs with Grafana Cloud but notes that there is no native integration and that a proxy would be required to forward logs. |
• The speaker discusses how Loki in Grafana Cloud can process log data into usable metrics, such as request rates, error rates, and latencies. |
• Deploying Promptail as a daemon set and sending logs to Loki |
• Instrumenting application code with Prometheus client library |
• Collecting metrics from database (e.g. MySQL) using exporter |
• Organizing dashboards in a consistent format (e.g. request rates, error rates, latency) |
• Using mixin packaging format for distributing dashboards and alerts |
• Referencing Cortex or Kubernetes mixins as examples |
• Challenges in using JSON for changelogs due to version differences between languages (e.g. Go, Python, JavaScript) |
• Introduction of mixins as an advanced feature for packaging and redistributing software components |
• Advantages of JSON it bundler tools (MixTool, Grizzly, Tanker) for managing complex configurations |
• Use of a single repository for config management in Grafana Cloud with Kubernetes clusters |
• Managing Kubernetes jobs using JSON it |
• Discussion of the vision for delivering dashboards, alerts, and applications as a single package |
• Criticism that this approach is too hard to use and may not be suitable for most people |
• Introduction of a more opinionated and integrated version of JSON it in Grafana Cloud |
• Simplification of configuration through the Grafana agent and its integration with various exporters. |
• JSON it bundler |
• Grafana agent vs Prometheus operator |
• Challenges with dashboard integration in Grafana |
• Best practices for building dashboards: |
• Templating data sources and job/instance labels |
• Using templates to dynamically discover jobs/metrics |
• Adding info metrics to software |
• Building dashboards as code using libraries (Grafana, Grafana Builder, Grafana Lib) |
• Version controlling dashboards from the start |
• Implementing GitOps style approach with tools like Grizzly |
• Discussing the use of Grafana with a JSON definition of a dashboard |
• Implementing dev deploy cycle on a laptop for developing dashboards and uploading them to Grafana |
• Version controlling source code instead of JSON files for reviewability and collaboration |
• The 80/20 rule for Grafana usage, where 80% is easy-to-use editing and 20% is advanced SRE/DevOps approach |
• Pair programming an hour-long YouTube stream to capture the advanced approach |
• Discussing VS Code Sharing and Rufana Cloud/Rufana Agent integration |
• Importance of capturing and sharing the advanced approach for others to learn from it |
• Barriers to entry for tracing vs logs |
• Challenges in the tracing space due to high investment and instrumentation requirements |
• Benefits of tracing, particularly in performance challenges |
• Open Telemetry and its tracing stack |
• Auto-instrumentation in various languages (e.g. Java, Python) |
• Distributed tracing and blind spots in instrumented stacks |
• Tracing in load balancers and CDNs (e.g. AWS ELBs, Fastly) |
• Distributed tracing and spans in software applications |
• Instrumenting Elixir server and client for better understanding of request flow |
• Challenges in getting complete traces from all services and the effort-reward trade-off |
• Focusing on key hops in the application stack (e.g. Ingress Nginx, Kubernetes service, application) |
• Potential limitations of adding spans to certain layers (e.g. load balancer, TCP level) |
• Using OpenTelemetry for vendor-neutral tracing standards and potential for adding spans to open-source projects |
• Creating Grafana dashboards for visualization of request flow and exploring different tools and version control systems |
• Iterating on solving specific observability problems |
• Long-term value of integrating tempo and other tools |
• Ecosystem maturity and changing tooling landscape |
• Big tent philosophy in observability and data sources |
• Grafana Labs' mission to support multiple tooling choices |
• Origin of the term "big tent" and its application in Grafana |
[0.00 --> 4.78] Hey, how's it going? I'm your host, Gerhard Lassou, and you're listening to Ship It, |
[5.04 --> 9.96] a podcast about getting your best ideas into the world and seeing what happens. |
[10.28 --> 16.04] We talk about code, ops, infrastructure, and the people that make it happen. Yes, |
[16.26 --> 20.62] we focus on the people because everything else is an implementation detail. |
[21.06 --> 25.98] I last spoke to Tom in Changelog episode 375 when I went to my first KubeCon. |
[25.98 --> 31.38] So many things changed since then. The one thing that didn't change is me using Grafana on a daily |
[31.38 --> 38.30] basis. But what is this new thing called Loki? And what about Tempo? While the 2021 Changelog.com |
[38.30 --> 44.18] setup uses Grafana Agent with Prometheus and Loki via Grafana Cloud, we don't use Tempo. Yet. |
[44.58 --> 48.78] By the way, are you curious to know how Grafana Cloud can offer such a generous free tier? |
[49.26 --> 54.90] Tom has a really good answer. The solution is built into the Cortex architecture. And yes, |
[54.90 --> 58.98] Cortex is the reason why we have a VP of product on Ship It in the first place. |
[59.38 --> 63.76] Anyways, would you like to watch me and Tom pair and build Grafana dashboards like pros? |
[64.12 --> 69.04] Tom has this really interesting approach that I would like to learn too. We can either live pair |
[69.04 --> 74.18] or record and then publish the video. Let me know your preference via our Changelog Slack |
[74.18 --> 79.62] or just plain Twitter. Otherwise, I'll just pick one at random. I recommend that you listen to this |
[79.62 --> 85.20] episode in combination with episodes three and 11. That's the best way to get a more complete |
[85.20 --> 90.72] picture of the topics that we discussed today. Big thanks to our partners Fastly, LaunchDarkly, |
[90.84 --> 96.88] and Linode. Our bandwidth is provided by Fastly, learn more at Fastly.com, feature flags powered by |
[96.88 --> 103.70] LaunchDarkly.com, and we love Linode. They keep it fast and simple. Check them out at linode.com |
[103.70 --> 104.90] forward slash changelog. |
[110.90 --> 116.64] What's up, shippers? This episode is brought to you by our friends at Fly. Fly lets you deploy your |
[116.64 --> 123.98] apps and databases close to your users in minutes. You can run your Ruby, Go, Node, Deno, Python, |
[124.48 --> 130.48] or Elixir app and databases all over the world. No ops required. Fly's vision is that all apps should |
[130.48 --> 135.02] run close to their users. They have generous free tiers for most services, so you can easily prove |
[135.02 --> 139.68] to yourself and your team that the Fly platform has everything you need to run your app globally. |
[140.10 --> 144.74] Learn more at fly.io slash changelog and check out the speedrun and their excellent docs. |
[145.14 --> 148.50] Again, fly.io slash changelog or check the show notes for links. |
[151.68 --> 155.60] We are going to shift in three, two, one. |
[155.60 --> 174.62] Last time that we spoke, Tom, was at KubeCon 2019 North America. That was actually my first |
[174.62 --> 180.50] KubeCon in San Diego, and it was an amazing one. I loved it. This was actually changelog episode |
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